James T. Kwok

According to our database1, James T. Kwok authored at least 185 papers between 1995 and 2018.

Collaborative distances :
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2018
Fast-Solving Quasi-Optimal LS-S3VM Based on an Extended Candidate Set.
IEEE Trans. Neural Netw. Learning Syst., 2018

Multi-Label Learning with Global and Local Label Correlation.
IEEE Trans. Knowl. Data Eng., 2018

Scalable Online Convolutional Sparse Coding.
IEEE Trans. Image Processing, 2018

Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data.
CoRR, 2018

Power Law in Sparsified Deep Neural Networks.
CoRR, 2018

Online Convolutional Sparse Coding with Sample-Dependent Dictionary.
CoRR, 2018

Loss-aware Weight Quantization of Deep Networks.
CoRR, 2018

Learning with Heterogeneous Side Information Fusion for Recommender Systems.
CoRR, 2018

Online Convolutional Sparse Coding with Sample-Dependent Dictionary.
Proceedings of the 35th International Conference on Machine Learning, 2018

Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
A Note on the Unification of Adaptive Online Learning.
IEEE Trans. Neural Netw. Learning Syst., 2017

Multi-Label learning in the independent label sub-spaces.
Pattern Recognition Letters, 2017

Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
Journal of Machine Learning Research, 2017

Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers.
CoRR, 2017

Multi-Label Learning with Global and Local Label Correlation.
CoRR, 2017

Accelerated and Inexact Soft-Impute for Large-Scale Matrix and Tensor Completion.
CoRR, 2017

Online Convolutional Sparse Coding.
CoRR, 2017

Zero-shot learning with a partial set of observed attributes.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Follow the Moving Leader in Deep Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Collaborative Filtering with Social Local Models.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Fast Learning with Nonconvex L1-2 Regularization.
CoRR, 2016

Learning of Generalized Low-Rank Models: A Greedy Approach.
CoRR, 2016

Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
CoRR, 2016

Loss-aware Binarization of Deep Networks.
CoRR, 2016

Fast Nonsmooth Regularized Risk Minimization with Continuation.
CoRR, 2016

Fast-and-Light Stochastic ADMM.
CoRR, 2016

Aggregating Crowdsourced Ordinal Labels via Bayesian Clustering.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Greedy Learning of Generalized Low-Rank Models.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Fast-and-Light Stochastic ADMM.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Asynchronous Distributed Semi-Stochastic Gradient Optimization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Towards Safe Semi-Supervised Learning for Multivariate Performance Measures.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Efficient Learning of Timeseries Shapelets.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Fast Nonsmooth Regularized Risk Minimization with Continuation.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Machine Learning.
Proceedings of the Springer Handbook of Computational Intelligence, 2015

Scaling Up Graph-Based Semisupervised Learning via Prototype Vector Machines.
IEEE Trans. Neural Netw. Learning Syst., 2015

Large-Scale Nyström Kernel Matrix Approximation Using Randomized SVD.
IEEE Trans. Neural Netw. Learning Syst., 2015

Scalable Nonparametric Low-Rank Kernel Learning Using Block Coordinate Descent.
IEEE Trans. Neural Netw. Learning Syst., 2015

Bayes-Optimal Hierarchical Multilabel Classification.
IEEE Trans. Knowl. Data Eng., 2015

Fast Distributed Asynchronous SGD with Variance Reduction.
CoRR, 2015

Fast Low-Rank Matrix Learning with Nonconvex Regularization.
CoRR, 2015

Fast Second Order Stochastic Backpropagation for Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Collaborative filtering via co-factorization of individuals and groups.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Accelerated Inexact Soft-Impute for Fast Large-Scale Matrix Completion.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Fast Low-Rank Matrix Learning with Nonconvex Regularization.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Colorization by Patch-Based Local Low-Rank Matrix Completion.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification.
IEEE Trans. Neural Netw. Learning Syst., 2014

Simple randomized algorithms for online learning with kernels.
Neural Networks, 2014

Selected papers from the 2011 International Conference on Neural Information Processing (ICONIP 2011).
Neurocomputing, 2014

Learning to Predict from Crowdsourced Data.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Fast Stochastic Alternating Direction Method of Multipliers.
Proceedings of the 31th International Conference on Machine Learning, 2014

Asynchronous Distributed ADMM for Consensus Optimization.
Proceedings of the 31th International Conference on Machine Learning, 2014

Accelerated Stochastic Gradient Method for Composite Regularization.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Gradient Descent with Proximal Average for Nonconvex and Composite Regularization.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Accurate Integration of Aerosol Predictions by Smoothing on a Manifold.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Multilabel Classification with Label Correlations and Missing Labels.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Convex and scalable weakly labeled SVMs.
Journal of Machine Learning Research, 2013

Convex and Scalable Weakly Labeled SVMs
CoRR, 2013

Fast Stochastic Alternating Direction Method of Multipliers.
CoRR, 2013

Accurate Probability Calibration for Multiple Classifiers.
Proceedings of the IJCAI 2013, 2013

Efficient Kernel Learning from Side Information Using ADMM.
Proceedings of the IJCAI 2013, 2013

Flexible Nonparametric Kernel Learning with Different Loss Functions.
Proceedings of the Neural Information Processing - 20th International Conference, 2013

Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels.
Proceedings of the 30th International Conference on Machine Learning, 2013

Efficient Multi-label Classification with Many Labels.
Proceedings of the 30th International Conference on Machine Learning, 2013

Efficient Learning for Models with DAG-Structured Parameter Constraints.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Learning from High-Dimensional Data in Multitask/Multilabel Classification.
Proceedings of the 2nd IAPR Asian Conference on Pattern Recognition, 2013

2012
Efficient Sparse Modeling With Automatic Feature Grouping.
IEEE Trans. Neural Netw. Learning Syst., 2012

Bilinear Probabilistic Principal Component Analysis.
IEEE Trans. Neural Netw. Learning Syst., 2012

A brief introduction to the special issue for ISNN2010.
Neurocomputing, 2012

Convex Multitask Learning with Flexible Task Clusters
CoRR, 2012

Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Convex Multitask Learning with Flexible Task Clusters.
Proceedings of the 29th International Conference on Machine Learning, 2012

Hierarchical Multilabel Classification with Minimum Bayes Risk.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

2011
A Hybrid PSO-BFGS Strategy for Global Optimization of Multimodal Functions.
IEEE Trans. Systems, Man, and Cybernetics, Part B, 2011

Domain Adaptation via Transfer Component Analysis.
IEEE Trans. Neural Networks, 2011

Incorporating cellular sorting structure for better prediction of protein subcellular locations.
J. Exp. Theor. Artif. Intell., 2011

Structured clustering with automatic kernel adaptation.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Efficient Sparse Modeling with Automatic Feature Grouping.
Proceedings of the 28th International Conference on Machine Learning, 2011

MultiLabel Classification on Tree- and DAG-Structured Hierarchies.
Proceedings of the 28th International Conference on Machine Learning, 2011

Time and space efficient spectral clustering via column sampling.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010
Incorporating the loss function into discriminative clustering of structured outputs.
IEEE Trans. Neural Networks, 2010

Clustered Nyström method for large scale manifold learning and dimension reduction.
IEEE Trans. Neural Networks, 2010

Simplifying mixture models through function approximation.
IEEE Trans. Neural Networks, 2010

Fast and accurate kernel density approximation using a divide-and-conquer approach.
Journal of Zhejiang University - Science C, 2010

Text detection in images using sparse representation with discriminative dictionaries.
Image Vision Comput., 2010

Spectral and Semidefinite Relaxation of the CLUHSIC Algorithm.
Proceedings of the SIAM International Conference on Data Mining, 2010

Manifold regularization for structured outputs via the joint kernel.
Proceedings of the International Joint Conference on Neural Networks, 2010

Making Large-Scale Nyström Approximation Possible.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Online multiple instance learning with no regret.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Cost-Sensitive Semi-Supervised Support Vector Machine.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Maximum Margin Clustering Made Practical.
IEEE Trans. Neural Networks, 2009

Building Sparse Multiple-Kernel SVM Classifiers.
IEEE Trans. Neural Networks, 2009

Maximum Penalized Likelihood Kernel Regression for Fast Adaptation.
IEEE Trans. Audio, Speech & Language Processing, 2009

Density-Weighted Nyström Method for Computing Large Kernel Eigensystems.
Neural Computation, 2009

Tighter and Convex Maximum Margin Clustering.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Multiple Kernel Clustering.
Proceedings of the SIAM International Conference on Data Mining, 2009

A Convex Method for Locating Regions of Interest with Multi-instance Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Accelerated Gradient Methods for Stochastic Optimization and Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Domain Adaptation via Transfer Component Analysis.
Proceedings of the IJCAI 2009, 2009

Prototype vector machine for large scale semi-supervised learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Semi-supervised learning using label mean.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Maximum Margin Clustering with Multivariate Loss Function.
Proceedings of the ICDM 2009, 2009

Accelerated Gradient Method for Multi-task Sparse Learning Problem.
Proceedings of the ICDM 2009, 2009

Unsupervised Maximum Margin Feature Selection with manifold regularization.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008
Matrix-Variate Factor Analysis and Its Applications.
IEEE Trans. Neural Networks, 2008

Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines.
IEEE Trans. Neural Networks, 2008

Improved Nyström low-rank approximation and error analysis.
Proceedings of the Machine Learning, 2008

Transferring Localization Models across Space.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

Transfer Learning via Dimensionality Reduction.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
A Class of Single-Class Minimax Probability Machines for Novelty Detection.
IEEE Trans. Neural Networks, 2007

Face recognition using spectral features.
Pattern Recognition, 2007

SVDD-Based Pattern Denoising.
Neural Computation, 2007

Surrogate maximization/minimization algorithms and extensions.
Machine Learning, 2007

End-to-end privacy control in service outsourcing of human intensive processes: A multi-layered Web service integration approach.
Information Systems Frontiers, 2007

Ensembles of Partially Trained SVMs with Multiplicative Updates.
Proceedings of the IJCAI 2007, 2007

Marginalized Multi-Instance Kernels.
Proceedings of the IJCAI 2007, 2007

Maximum margin clustering made practical.
Proceedings of the Machine Learning, 2007

Simpler core vector machines with enclosing balls.
Proceedings of the Machine Learning, 2007

Adaptive Localization in a Dynamic WiFi Environment through Multi-view Learning.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Generalized Core Vector Machines.
IEEE Trans. Neural Networks, 2006

Efficient hyperkernel learning using second-order cone programming.
IEEE Trans. Neural Networks, 2006

Multidimensional Vector Regression for Accurate and Low-Cost Location Estimation in Pervasive Computing.
IEEE Trans. Knowl. Data Eng., 2006

Embedded kernel eigenvoice speaker adaptation and its implication to reference speaker weighting.
IEEE Trans. Audio, Speech & Language Processing, 2006

Model-based transductive learning of the kernel matrix.
Machine Learning, 2006

Simplifying Mixture Models through Function Approximation.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Large-Scale Sparsified Manifold Regularization.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Efficient kernel feature extraction for massive data sets.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

Learning the Kernel in Mahalanobis One-Class Support Vector Machines.
Proceedings of the International Joint Conference on Neural Networks, 2006

Wavelet-Based Feature Extraction for Microarray Data Classification.
Proceedings of the International Joint Conference on Neural Networks, 2006

Efficient Classification of Multi-label and Imbalanced Data using Min-Max Modular Classifiers.
Proceedings of the International Joint Conference on Neural Networks, 2006

Multimodal Registration using the Discrete Wavelet Frame Transform.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Gene Feature Extraction Using T-Test Statistics and Kernel Partial Least Squares.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

Block-quantized kernel matrix for fast spectral embedding.
Proceedings of the Machine Learning, 2006

Locally adaptive classification piloted by uncertainty.
Proceedings of the Machine Learning, 2006

A regularization framework for multiple-instance learning.
Proceedings of the Machine Learning, 2006

Facial Image Reconstruction by SVDD-Based Pattern De-noising.
Proceedings of the Advances in Biometrics, International Conference, 2006

Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Diversified SVM Ensembles for Large Data Sets.
Proceedings of the Machine Learning: ECML 2006, 2006

Accelerated Convergence Using Dynamic Mean Shift.
Proceedings of the Computer Vision, 2006

2005
Kernel Eigenvoice Speaker Adaptation.
IEEE Trans. Speech and Audio Processing, 2005

Core Vector Machines: Fast SVM Training on Very Large Data Sets.
Journal of Machine Learning Research, 2005

Accurate and Low-cost Location Estimation Using Kernels.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Core Vector Regression for very large regression problems.
Proceedings of the Machine Learning, 2005

Position estimation for wireless sensor networks.
Proceedings of the Global Telecommunications Conference, 2005. GLOBECOM '05, St. Louis, Missouri, USA, 28 November, 2005

Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

Very Large SVM Training using Core Vector Machines.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

Towards end-to-end privacy control in the outsourcing of marketing activities: a web service integration solution.
Proceedings of the 7th International Conference on Electronic Commerce, 2005

2004
Fusing images with different focuses using support vector machines.
IEEE Trans. Neural Networks, 2004

The pre-image problem in kernel methods.
IEEE Trans. Neural Networks, 2004

Dissimilarity learning for nominal data.
Pattern Recognition, 2004

Speedup of kernel eigenvoice speaker adaptation by embedded kernel PCA.
Proceedings of the INTERSPEECH 2004, 2004

Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm.
Proceedings of the Machine Learning, 2004

Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model.
Proceedings of the Machine Learning, 2004

A study of various composite kernels for kernel eigenvoice speaker adaptation.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Incremental PCA based face recognition.
Proceedings of the 8th International Conference on Control, 2004

Efficient Hyperkernel Learning Using Second-Order Cone Programming.
Proceedings of the Machine Learning: ECML 2004, 2004

Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo.
Proceedings of the Nineteenth National Conference on Artificial Intelligence, 2004

2003
Linear dependency between ε and the input noise in ε-support vector regression.
IEEE Trans. Neural Networks, 2003

Texture classification using the support vector machines.
Pattern Recognition, 2003

Mining customer product ratings for personalized marketing.
Decision Support Systems, 2003

Eigenvoice Speaker Adaptation via Composite Kernel PCA.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Parametric Distance Metric Learning with Label Information.
Proceedings of the IJCAI-03, 2003

The Pre-Image Problem in Kernel Methods.
Proceedings of the Machine Learning, 2003

Learning with Idealized Kernels.
Proceedings of the Machine Learning, 2003

2002
Multifocus image fusion using artificial neural networks.
Pattern Recognition Letters, 2002

Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images.
Information Fusion, 2002

Improving De-Noising by Coefficient De-Noising and Dyadic Wavelet Transform.
Proceedings of the 16th International Conference on Pattern Recognition, 2002

Fusing Images with Multiple Focuses Using Support Vector Machines.
Proceedings of the Artificial Neural Networks, 2002

2001
Combination of images with diverse focuses using the spatial frequency.
Information Fusion, 2001

Linear Dependency between epsilon and the Input Noise in epsilon-Support Vector Regression.
Proceedings of the Artificial Neural Networks, 2001

Applying the Bayesian Evidence Framework to \nu -Support Vector Regression.
Proceedings of the Machine Learning: EMCL 2001, 2001

Bayesian Support Vector Regression.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
The evidence framework applied to support vector machines.
IEEE Trans. Neural Netw. Learning Syst., 2000

Rival Penalized Competitive Learning for Model-Based Sequence Clustering.
Proceedings of the 15th International Conference on Pattern Recognition, 2000

1999
Moderating the outputs of support vector machine classifiers.
IEEE Trans. Neural Networks, 1999

Moderating the outputs of support vector machine classifiers.
Proceedings of the International Joint Conference Neural Networks, 1999

Integrating the evidence framework and the support vector machine.
Proceedings of the ESANN 1999, 1999

1998
Automated Text Categorization Using Support Vector Machine.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998

1997
Objective functions for training new hidden units in constructive neural networks.
IEEE Trans. Neural Networks, 1997

Constructive algorithms for structure learning in feedforward neural networks for regression problems.
IEEE Trans. Neural Networks, 1997

1996
Use of bias term in projection pursuit learning improves approximation and convergence properties.
IEEE Trans. Neural Networks, 1996

Bayesian Regularization in Constructive Neural Networks.
Proceedings of the Artificial Neural Networks, 1996

1995
Improving the approximation and convergence capabilities of projection pursuit learning.
Neural Processing Letters, 1995


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